Changes in the Relationship between Particulate Matter and Surface Temperature in Seoul from 2002–2017

• Main Author: Minjoong J. Kim
• Format: Article
• Language: English
• Published: MDPI AG 2019-05-01
• Series: Atmosphere
• Subjects: particulate matter; climate change; air pollution meteorology; air quality
• Online Access: https://www.mdpi.com/2073-4433/10/5/238

This study focuses on the changes over time in the relationship between surface temperature and particulate matter (PM) concentration over Seoul using long-term observational data. Correlation coefficients between the daily mean PM₁₀ concentration and surface temperature were calculated to investigate the relationship between the two. The PM₁₀ and temperature displayed a strong positive correlation, suggesting the increase in PM was driven by large-scale synoptic patterns accompanying such high temperatures. It was found that the correlation coefficient in 2002−2009 was significantly higher than that of 2010−2017, indicating that the relationship between PM₁₀ concentration and temperature has weakened over time in recent decades. Correlation coefficients between daily averaged temperature and the PM₁₀ of each year were calculated to account for the decreased correlation in the most recent decade. We found that the correlation coefficients between surface temperature and PM of each year exhibited a clear negative correlation with the longitudinal position of the Siberian High, suggesting that the position of the Siberian High might affect the strength of the relationship between PM concentration and temperature over Seoul. We also found that the eastward shift of the Siberian High reduces the standard deviation of pressure over Seoul, indicating reduction of synoptic perturbation. These results imply that the eastward shift of the Siberian High in recent decades might weaken the relationship between the PM and surface temperature over Seoul. This study suggests that the relationship between PM and meteorological variables is changing over time through changes in large climate variability.